There are a number of human diseases that are
caused by the epistatic interaction of multiple genes. Detecting
these interactions with standard statistical tools is
difficult, because there may be an interaction effect, but
minimal or no main effect. Reconstructability analysis uses
Shannon's information theory to detect relationships between
variables in categorical datasets. We apply reconstructability
analysis to data generated by five different
models of gene-gene interaction, with heritability levels
from 0.053 to 0.008, using 200 controls and 200 cases. We
find that even with heritability levels as low as 0.008, and
with the inclusion of 50 non-associated genes in the dataset,
we can identify the interacting gene pairs with an accuracy
of 80% or better.